Building a Scripted ETL Pipeline

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Learn how to script, automate, and manage data pipelines through this comprehensive course in the Data Engineering Skill Path. You will develop critical competencies, including cleaning and transforming data using Python, combining datasets from multiple sources, performing scripted extraction and loading tasks, retrieving external data through APIs, and using database-native tools to carry out bulk ingestion into a cloud warehouse. Through hands-on practice with Python, Tableau, Microsoft tools, IBM API workflows, and Snowflake, you will learn to build reliable, repeatable ETL processes that move data from raw form to structured, analysis-ready outputs. This course combines expertise from Fractal Analytics, Tableau, Microsoft, IBM, and Snowflake, offering multiple perspectives on the ETL lifecycle. You will progress from foundational data wrangling to merge and join operations, scripting data processing tasks, collecting external data, and finally scaling ingestion using enterprise-grade cloud tooling. The curriculum balances conceptual understanding with practical exercises, preparing you to confidently script and manage ETL pipelines across diverse platforms. Perfect for aspiring data engineers and learners seeking strong, practical skills in automated data transformation and pipeline development.

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